Gao Xinyan, Lin Yanling, Zhang Jun, Jiang Xiaoxiang, Wu Riping, Zhong Dongta
Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Clinical Medical School of Fujian Medical University, Fuzhou, Fujian, China.
Nutr Cancer. 2025;77(3):405-413. doi: 10.1080/01635581.2024.2445870. Epub 2025 Jan 2.
Ovarian cancer is a lethal female cancer with a rising incidence that is often diagnosed late due to a lack of symptoms, affecting survival and quality of life. Studies suggest that dietary factors, especially the levels of branched-chain amino acids such as valine, may influence its development. While valine is essential for metabolism, its specific role in ovarian cancer remains unclear, necessitating further research.
This study aimed to elucidate the causal relationship between valine and OC through a bidirectional Mendelian randomization (MR) approach. Data were sourced from the IEU OpenGWAS project, encompassing genome-wide association statistics for valine ( = 115,048) and OC (Ncase = 1,218, Ncontrol = 198,523) among European participants. Independent genetic variants associated with each phenotype at genome-wide significance were employed as instrumental variables (IVs). The primary analysis utilized the inverse variance weighted (IVW) method for two-sample MR analysis. MR‒Egger regression was applied to adjust for potential pleiotropy, whereas the weighted median method provided robust causal estimates under the assumption of valid IVs. Sensitivity analyses, including leave-one-out (LOO) analysis, heterogeneity tests, and horizontal pleiotropy assessments, were conducted to ensure the robustness of the findings.
The results revealed a significant causal relationship between valine and OC, identifying valine as a risk factor for OC ( = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249) in the forward MR analysis. Sensitivity analyses confirmed the absence of heterogeneity (Q_p value >0.05) and horizontal pleiotropy ( > 0.05), and LOO analysis validated the stability of the results. Conversely, reverse MR analysis revealed no causal effect of OC on valine levels ( = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528).
These findings reveal a causal link between high valine levels and an increased OC risk. This research highlights the monitoring of valine levels as a preventive strategy and the significance of valine metabolism in OC. Future studies are needed to investigate the mechanisms and interventions for reducing risk, offering insights for clinical practice and public health initiatives in OC prevention.
卵巢癌是一种致命的女性癌症，发病率呈上升趋势，由于缺乏症状，往往在晚期才被诊断出来，影响生存和生活质量。研究表明，饮食因素，尤其是缬氨酸等支链氨基酸的水平，可能会影响其发展。虽然缬氨酸对新陈代谢至关重要，但其在卵巢癌中的具体作用仍不清楚，需要进一步研究。
本研究旨在通过双向孟德尔随机化（MR）方法阐明缬氨酸与卵巢癌之间的因果关系。数据来源于IEU OpenGWAS项目，包括欧洲参与者中缬氨酸（n = 115,048）和卵巢癌（病例数 = 1,218，对照数 = 198,523）的全基因组关联统计数据。在全基因组显著性水平上与每种表型相关的独立遗传变异被用作工具变量（IVs）。主要分析采用逆方差加权（IVW）方法进行两样本MR分析。MR-Egger回归用于调整潜在的多效性，而加权中位数方法在有效IVs的假设下提供了稳健的因果估计。进行了敏感性分析，包括留一法（LOO）分析、异质性检验和水平多效性评估，以确保研究结果的稳健性。
结果显示缬氨酸与卵巢癌之间存在显著的因果关系，在前瞻性MR分析中确定缬氨酸为卵巢癌的一个风险因素（β = 0.043，95%CI = 1.00008 - 1.00491，OR = 1.00249）。敏感性分析证实不存在异质性（Q_p值 > 0.05）和水平多效性（P > 0.05），并且LOO分析验证了结果的稳定性。相反，反向MR分析显示卵巢癌对缬氨酸水平没有因果效应（β = 0.875，95%CI = 0.34125 - 2.51495，OR = 1.08528）。
这些发现揭示了高缬氨酸水平与卵巢癌风险增加之间的因果联系。本研究强调监测缬氨酸水平作为一种预防策略以及缬氨酸代谢在卵巢癌中的重要性。未来需要研究降低风险的机制和干预措施，为卵巢癌预防的临床实践和公共卫生举措提供见解。
